水平集重构方法改进及亚像素边缘定位

常用的亚像素边缘定位算法采取局部表面估计或结构模型实现局部边缘的定位,不可避免由于离散化导致的锯齿效应和由于局部模型带来的不连续边缘定位。为此在扩散方程的基础上提出了一种改进的水平集重构算法,通过改进的水平集重构实现边缘沿切线方向的平滑;加入角点定位判断,在角点处加入角点限制和拓扑限制以保证角点处的精确定位。通过几何图像和自然图像的亚像素边缘提取对比实验,验证了该算法能在保持亚像素精度的同时消除锯齿效应,保持边缘的平滑和连续性。

Subpixel Edge Location Using Improved LSR

Traditional subpixel edge location algorithms use local model to realize precise edge location.Which leads to side effects such as Zigzag effect and discontinuous edges.We present a new subpixel edge location algorithm based on partial differential equation(PDE),where level-set reconstruction(LSR) is introduced to smooth edge along their tangents.Anchor and topology constraints are used to avoid over-smoothing and keep edge topology structures.Subpixel edge location experiments with both geometric and natural image show that this method can remove zigzag effect while keeping edge smoothness and continuity.